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中国能源-粮食生产对水资源竞争的关系——基于水足迹的视角 被引量:20

Study on the competitive relationship between energy and food production for water resources in China:From a perspective of water footprint
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摘要 通过对水-能源-粮食系统的定量分析,能更好的探究三者之间的协同作用,对提高区域资源综合利用效率、促进区域可持续发展具有重要意义。本文基于水足迹视角探讨了1990—2017年中国31个地区能源-粮食生产对水资源的竞争关系,并借助ESTDA模型框架对其时空动态特征进行分析。结果表明:①中国化石能源水足迹的时间演变特征可分为缓慢下降-快速上升-平稳下降3个阶段,其中化石能源灰水足迹平均占化石能源水足迹的70%以上;电力水足迹呈持续上升态势,其中电力蓝水足迹平均占电力水足迹的70%以上;粮食蓝水足迹上升幅度明显,平均占农业用水总量的70%以上。②能源-粮食水足迹总量空间分布格局受区域资源禀赋差异影响较大。③时间序列上,中国能源-粮食生产对水资源竞争指数呈逐年上升态势;空间分布上,同时兼顾能源生产与粮食生产的黄河中下游区、东北地区为竞争指数高值集聚区,其余地区竞争指数相对较小。④LISA时间路径分析显示,中国南方地区能源-粮食水资源竞争指数的空间格局的稳定性比北方更强;各地区在不同程度上均受局部结构的时空依赖效应影响;竞争指数空间格局变化具有较强的整合性且空间凝聚性较强。⑤能源-粮食生产对水资源的竞争在短期内难以得到有效缓解。 Water,energy and food(WEF)are key elements of economic and social sustainable development.In China,water security is the most prominent problem in the WEF-nexus,which is manifested in the competitive relationship between food and energy production for water.Therefore,the matter of alleviating water resources stress and pressure has become a hot issue.In this paper,we measured the water footprint of major energy(coal,oil,natural gas),power(thermal power,hydropower nuclear power,wind power and solar power)generation,and food blue water footprint in 31 provincial-level regions of China from 1990 to 2017.Energy-food for water resources model and ESTDA model were used to analyze the competition state of energyfood for water resources and the dynamic characteristics of spatio-temporal pattern in the study period.The results showed that:(1)The temporal evolution of fossil water footprint in China can be divided into three stages:slow decline,rapid rise and steady decline.The water footprint of electricity showed a continuous upward trend,and the average blue water footprint of electricity contributed more than 70%.Blue water footprint of food increased significantly,accounting for more than 70%of the total agricultural water used.(2)On the spatial distribution,high values of fossil energy water footprint are mainly observed in the areas with abundant coal,oil and gas resources;the power water footprint is roughly in the thermal power and hydropower gathering area bounded by the"Bo-Tai line"(Bole city-Taipei city),and other electricity water footprint accounts for less than 2%.The high value areas of blue water footprint of grain are mainly concentrated on the east side of the Heihe-Tengchong Line.(3)On time series,China’s energy-food water resources competition index has increased year by year,from 0.22 in the early stage to 0.53 in the late stage.On the spatial distribution,the middle and lower reaches of the Yellow River and Northeast China,considering energy production and grain production,are the gathering areas with a relatively high competition index,while the remaining regions have a relatively small competition index.(4)LISA time path analysis showed that the spatial pattern of energy-food water resources competition index in southern China is more stable than that in northern China.All regions are affected by spatio-temporal dependence of local structure to varying degrees.The LISA spatial and temporal transition showed that the energy-food water resources competition index in various regions has strong spatial cohesion,and there are certain path dependence and locking characteristics.The results can provide reference for the coordinated development of regional energy,food production and water resources,and will help the government to make some effective policies.(5)The competition between energy and food production for water resources is difficult to be effectively alleviated in the short term.
作者 郝帅 孙才志 宋强敏 HAO Shuai;SUN Caizhi;SONG Qiangmin(School of Geography,Liaoning Normal University,Dalian 116029,Liaoning,China;Center for Studies of Marine Economy and Sustainable Development,Liaoning Normal University,Dalian 116029,Liaoning,China)
出处 《地理研究》 CSSCI CSCD 北大核心 2021年第6期1565-1581,共17页 Geographical Research
基金 国家社会科学基金重点项目(19AJY010)。
关键词 水足迹 水-能源-粮食关联 竞争关系 ESTDA模型 时空分析 中国 water footprint water-energy-food nexus competition relationship ESTDA model spatio-temporal analysis China
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